Early Career HEPEX Activity at the HEPEX 2025 Workshop: An Interactive Discussion on Tools, Resources & Skill Gaps in Hydrological Forecasting

An Early Career HEPEX session on “Interactive Discussion on Tools, Resources, and Skill Gaps in Hydrological Forecasting” was organized on the last day of the HEPEX 2025 workshop. This session welcomed everyone (not just early careers) and fostered an interactive discussion to share tools and resources while identifying learning and skill gaps in career paths related to hydrological forecasting. We created a hydrological forecasting chain online. After introducing the concept, participants were invited to contribute to the chain by engaging with four key themes/questions.

The four prompts were:

• Software tools: What software tools do you use or know about for any part of the hydrological forecasting chain? Please specify the full name or DOI so others can find it afterward. 
• Educational resources: What educational resources do you use or recommend? This could be a great scientific article, book, video, online platform, community, or anything else – feel free to be creative! 
• Training opportunities: What training opportunities have you come across that could benefit others? This could include conferences, summer schools, university courses, hackathons, or other relevant experiences. 
• Skill gaps in job applications: Based on the following job ads, what gaps do you see between your current CV and the listed requirements? You can focus on a specific ad that interests you the most.

The results are available on the online Miro board here!

Participants identified a wide array of software tools across most parts of the hydrologic forecasting chain, especially for hydrological modeling, allowing users to choose the one(s) that suit(s) their needs most effectively. However, a key insight from the compiled Miro board is the presence of critical gaps along the forecasting chain, particularly when it comes to training and educational resources. Some of these gaps may be due to the workshop and the audience focus; HEPEX has historically centered on hydrological forecasting, which may explain the limited coverage of meteorological forecasts or climate projections. But these blind spots could also highlight broader scientific and operational challenges. In areas like benchmarking, evaluation, post-processing, and verification, while a plethora of tools and methods exist, could there be a noticeable lack of accessible training materials to support their understanding and implementation? More generally, these gaps highlight an important opportunity for the community to invest in capacity building and knowledge transfer across the full forecasting workflow.

For the fourth prompt, we shared job ads from different institutes that represent different sectors early careers may work in (e.g., operations, user-engagement, machine learning and academia). Based on these, we identified and discussed gaps between skill sets required in those ads and skills developed by early careers throughout their education. 

Job postings often list “communication skills” without much detail – but what does that actually mean? This should perhaps be clearer in job postings in the future, but for now here’s what we learned from a conversation with established scientists and hiring managers:

• It’s about clarity, not perfection: Employers want candidates who can express themselves clearly and answer questions concisely – not necessarily the most polished speakers.
• It’s also about fit: How you work with others, handle open-ended questions, and show authenticity matters just as much as your technical know-how.
• Presentation skills are rising: Scientists noted that overall presentation quality at conferences and workshops is improving, and they take notice.
• Flexibility is key: Job ads often leave room for varied backgrounds. If you’re bright, curious, and technically capable, you can often learn on the job – even in a new domain.
• Know more than the ad: Doing your homework on the hiring institution and asking informed questions in the interview can set you apart.
• Be visible and verifiable: Your GitHub and LinkedIn profiles, and even personal references, can make a major difference.
• Mind the confidence gap: Women still tend to undervalue their qualifications. This motivates some employers to keep job descriptions flexible and not overly prescriptive.

And finally, neither AI nor machine learning are headline requirements yet, but many new grads learn those skills nowadays. Hiring managers and chairs should consider incorporating this new skill into their job announcements to attract a wide array of applicants. Early career applicants should, in turn, note their skill level in both of these areas whether they are part of the job call or not.

If you have any ideas you’d like to contribute, feel free to add sticky notes directly to the Miro board!